84 machine-learning-phd Postdoctoral positions at Stanford University in Ireland-University-Ranking-2024
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applications, and ability to quickly learn and master various computer programs. Must be technically rigorous, organized, and have demonstrated excellence, innovation, and productivity in research. Ability
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. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
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statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data, including physiological waveforms and medical imaging. We foster a collaborative and
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. • Expertise in metabolomics with mass spectrometry is desired. • Strong general computer skills, experience with databases and scientific applications, and ability to quickly learn and master various computer
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to join an experienced mentor, lead independent projects, teach junior team members, and contribute to multidisciplinary research. We provide a supportive environment aimed at developing the scholar's
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engineering and clinical physiology. Projects may involve signal quality assessment, artifact detection, waveform segmentation, feature extraction, hemodynamic modeling, time-series analysis, machine learning
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for highly motivated postdoctoral candidates with a PhD in bioengineering deep knowledge in computational biology and machine learning. Candidates with a molecular biology or engineering degrees with
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groups from Stanford and beyond working on complementary approaches to T cell recognition. Our group provides an intellectually rich environment, with scientists applying genetics, proteomics and machine
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field Demonstrated expertise in one or more of the following areas: Machine/deep learning, artificial intelligence, statistical modeling, or computational modeling Human neuroimaging analysis, including
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outcomes for children with IBD. The successful candidate must hold a PhD, PharmD or MD/DO with a focus on pharmacometrics or computational biology/bioinformatics focused on -omics with an interest in